Book Image

Natural Language Understanding with Python

By : Deborah A. Dahl
5 (1)
Book Image

Natural Language Understanding with Python

5 (1)
By: Deborah A. Dahl

Overview of this book

Natural Language Understanding facilitates the organization and structuring of language allowing computer systems to effectively process textual information for various practical applications. Natural Language Understanding with Python will help you explore practical techniques for harnessing NLU to create diverse applications. with step-by-step explanations of essential concepts and practical examples, you’ll begin by learning about NLU and its applications. You’ll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you’ll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you’ll also discover practical issues such as acquiring data, evaluating systems, and deploying NLU applications along with their solutions. The book is a comprehensive guide that’ll help you explore techniques and resources that can be used for different applications in the future. By the end of this book, you’ll be well-versed with the concepts of natural language understanding, deep learning, and large language models (LLMs) for building various AI-based applications.
Table of Contents (21 chapters)
1
Part 1: Getting Started with Natural Language Understanding Technology
4
Part 2:Developing and Testing Natural Language Understanding Systems
16
Part 3: Systems in Action – Applying Natural Language Understanding at Scale

Cloud-based LLMs

Recently, there have been a number of cloud-based pretrained large language models that have shown very impressive performance because they have been trained on very large amounts of data. In contrast to BERT, they are too large to be downloaded and used locally. In addition, some are closed and proprietary and can’t be downloaded for that reason. These newer models are based on the same principles as BERT, and they have shown a very impressive performance. This impressive performance is due to the fact that these models have been trained with much larger amounts of data than BERT. Because they cannot be downloaded, it is important to keep in mind that they aren’t appropriate for every application. Specifically, if there are any privacy or security concerns regarding the data, it may not be a good idea to send it to the cloud for processing. Some of these systems are GPT-2, GPT-3, GPT-4, ChatGPT, and OPT-175B, and new LLMs are being published on a frequent...